This paper extends the model theory of RDF with rules, placing an emphasis on integration with OWL and decidability of entailstart from an abstract syntax that views a rule as a pa...
We propose a new machine learning paradigm called Graph Transformer Networks that extends the applicability of gradient-based learning algorithms to systems composed of modules th...
The recent explosion of interest in graph cut methods in computer vision naturally spawns the question: what energy functions can be minimized via graph cuts? This question was fi...
Occlusion is usually modelled in two images symmetrically in previous stereo algorithms which cannot work for multi-view stereo efficiently. In this paper, we present a novel form...
Abstract. Although there exist many polynomial algorithms for NPhard problems running on a bounded clique-width expression of the input graph, there exists only little comparable w...